The amount of digital data transmitting via interne
t has reached an enormous level. In order to conduc
t
efficient web data analysis, effective web mining t
ools are needed. Logos, which represent companies’
brands, are highly regarded in a business world.
These logos embedded in ordinary pictures could giv
e an
indication of popularity of the companies and their
products in a region. Therefore, it is imperative
to build
a computer system to extract company logos from the
se pictures. In this paper, a Logo on Map (LoM)
system is proposed, which consists of three modules
: picture extraction module (PEM), logo matching
module (LMM) and web mapping module (WMM). Only the
first two modules are covered in this paper.
The PEM is based on a keyword textual search while
the LMM is a visual search using SIFT (Scale-
Invariant Feature Transform) algorithm. The three e
xperiments are conducted using different sets of
pictures extracted from the Flickr® website. The ex
perimental results have proven that visual search i
s
more accurate than textual search and also demonstr
ated that LoM could be used to discover hidden
knowledge beyond logos.